Resource-Efficient Pareto-Optimal Green Scheduler Architecture

Resource-Efficient Pareto-Optimal Green Scheduler Architecture

Urmila Shrawankar, Chetan Ashokrao Dhule
Copyright: © 2022 |Pages: 14
DOI: 10.4018/IJCAC.305855
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Abstract

Rapidly developing cloud technology with enormous number of clients creates need of reducing power consumption of data centers. VM live migration is the most promising tool to achieve resource consolidation but it creates overheads in terms of additional CPU, disk I/O and network bandwidth utilization. This paper proposes a power-aware VM live migration based dynamic VM consolidation mechanism that focuses on reduction in datacenter’s resource utilization. Proposed mechanism is Pareto Optimal because during live migration it not only optimize the migration overheads but also select the VM and destination server by considering all the performance overheads to be generated during and after live migration. The proposed algorithm reduces nearly 60% of the VMs migration overheads. In terms of energy saving the proposed mechanism is 43% more efficient than the greedy scheduling approach and about 47% more energy efficient than the round-robin approach and thus achieves green computing goal.
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1. Introduction

IaaS model enables the customers to utilize the VMs as per their resource needs on pay-as-you-use model. This permits clients to run their applications on the most suitable and customized VMs and pay for the exact usage. Nonetheless, the resources provided by cloud suppliers in terms of CPU, memory, disc and network bandwidth always varies dynamically to fulfill dynamic demands of customer for resizing or termination of VMs. As an outcome, if cloud service providers fails to reallocate heterogeneous VMs and resources, a few hosts may become over-burden while other hosts might be underutilized. In the long run, such an uneven utilization of hosts brings about pointless initiation of servers, in this manner expanding the overall expenses.

Also, allocation of most of VMs to some over-burdened servers will potentially influences the QoS and causes SLA infringement. The VM live migration plays a vital role in VM consolidation, subsequently reallocate all the VMs into a couple of physical servers and power-off unutilized servers. This methodology improves the overall utilization of resources and permits energy saving while maintaining QoS.

A live-migration is an expensive activity. It causes additional network bandwidth utilization, CPU utilization and VM downtime. At the point when multiple VMs to be moved, it is imperative to plan the migrations wisely, so as to limit effect on QoS of both source and destination hosts and migrating VM.

VM migration issues are carefully examined, but we see that the VMs scheduling policies don't get a similar degree of consideration. It results in the inaccurate VM scheduling which leads to QoS degradation causing SLA infringement and we can't achieve the goal of energy saving with full accuracy.

This paper introduces POGS: Pareto-Optimal Green Scheduler, a live migration-based scheduler that efficiently calculates the migration overheads and selects the best host to achieve a seamless VM live migration. The assessment of POGS is performed over KVM based VMs as explained further sections.

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